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Record W2127659050 · doi:10.1186/1478-4505-11-39

Assessing communities of practice in health policy: a conceptual framework as a first step towards empirical research

2013· article· en· W2127659050 on OpenAlex
Maria Paola Bertone, Bruno Meessen, Guy Clarysse, David Hercot, Allison Gamble Kelley, Yamba Kafando, Isabelle L. Lange, Jérôme Pfaffmann, Valéry Ridde, Isidore Sieleunou, Sophie Witter

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHealth Research Policy and Systems · 2013
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsUniversité de Montréal
FundersEuropean CommissionUNICEF
KeywordsOperationalizationKnowledge managementHealth services researchHealth policyKnowledge translationTacit knowledgeHealth administrationEmpirical researchEmpirical evidenceConceptual frameworkKnowledge sharingSociologyPublic relationsComputer sciencePolitical scienceHealth careSocial science

Abstract

fetched live from OpenAlex

Communities of Practice (CoPs) are groups of people that interact regularly to deepen their knowledge on a specific topic. Thanks to information and communication technologies, CoPs can involve experts distributed across countries and adopt a 'transnational' membership. This has allowed the strategy to be applied to domains of knowledge such as health policy with a global perspective. CoPs represent a potentially valuable tool for producing and sharing explicit knowledge, as well as tacit knowledge and implementation practices. They may also be effective in creating links among the different 'knowledge holders' contributing to health policy (e.g., researchers, policymakers, technical assistants, practitioners, etc.). CoPs in global health are growing in number and activities. As a result, there is an increasing need to document their progress and evaluate their effectiveness. This paper represents a first step towards such empirical research as it aims to provide a conceptual framework for the analysis and assessment of transnational CoPs in health policy.The framework is developed based on the findings of a literature review as well as on our experience, and reflects the specific features and challenges of transnational CoPs in health policy. It organizes the key elements of CoPs into a logical flow that links available resources and the capacity to mobilize them, with knowledge management activities and the expansion of knowledge, with changes in policy and practice and, ultimately, with an improvement in health outcomes. Additionally, the paper addresses the challenges in the operationalization and empirical application of the framework.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Theoretical or conceptuallow
gptno category
Domain: not available · Genre: Other
About the Canadian research system: no · About a Canadian topic: no
Theoretical or conceptualhigh
models agreeAgreement compares identical category sets and study designs across arms.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.100
metaresearch head score (Gemma)0.100
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.830
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1000.100
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.006
Science and technology studies0.0060.002
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.006
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.927
GPT teacher head0.805
Teacher spread0.123 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it